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brain-cog

Brain-inspired Cognitive Intelligence Engine (BrainCog)

brainpy

BrainPy: a simulation toolbox for researches in computational neuroscience and brain-inspired computation

brian2stdpmnist

Brian 2 version of Paper "Unsupervised Learning of digit recognition using STDP"

contiki

The official git repository for Contiki, the open source OS for the Internet of Things

dnn_neurosim_v2.0

Benchmark framework of compute-in-memory based accelerators for deep neural network (on-chip training chip focused)

fist-use

just a try

fpga-proj

FPGA project

hands-on-session-snntorch-230302

learngit

IOT-hommework

lshort-zh-cn

A Chi­nese edi­tion of the Not So Short Introduction to LaTeX2ε

mlp_neurosim_v3.0

Benchmark framework of synaptic device technologies for a simple neural network

neuromorphic-computing-guide

Neuromorphic Computing Guide

neuromorphic-digit-classification

Simple Python simulation of a one-hidden-layer spiking neural network for digit classification on sklearn's "digits" dataset.

neuromorphic-hebbian-learning

Simple Python simulation of a single LIF neuron learning a digit pattern using Hebbian learning.

notes-python

中文 Python 笔记

notice-board

mmyun

snn-networking

Neuromorphic computing is a new technology which uses very-large-scale integration (VLSI) systems containing electrical analogs that mimic neurobiological structures. Such technology can be simulated using the Python framework snnTorch, a derivative of the deep learning framework PyTorch that has the capacity to run spiking neural networks (SNNs) w

snnformnist

A Spiking Neural Network Architecture for MNIST Digit Recognition

snntorch

Deep and online learning with spiking neural networks in Python

spiking-convnet

A Spiking Convolutional Neural Network implemented using brian2 package.

spiking-neural-network-snn-with-pytorch-where-backpropagation-engenders-stdp

What about coding a Spiking Neural Network using an automatic differentiation framework? In SNNs, there is a time axis and the neural network sees data throughout time, and activation functions are instead spikes that are raised past a certain pre-activation threshold. Pre-activation values constantly fades if neurons aren't excited enough.

stanford-tensorflow-tutorials

This repository contains code examples for the course CS 20SI: TensorFlow for Deep Learning Research.

stdp-mnist

stereospike

Stereo depth estimation with Spiking Neural Networks (SNN) on Dynamic Vision Sensor (DVS) data

sym-stdp-snn

Code for the model presented in the paper "A Biologically Plausible Supervised Learning Method for Spiking Neural Networks Using the Symmetric STDP Rule"

unsupervised-digit-recognition-using-spike-timing-dependent-plasticity

This project aims doing unsupervised learning of digit recognition task using Spiking neural network and Spike timing Dependent Plasticity so as to bring the representation of neural network more towards how actually the brain works. This project is still under progress.